High frequency deep brain stimulation attenuates subthalamic and cortical rhythms in Parkinson's disease

Globus pallidus externus drives increase in network-wide alpha power with propofol-induced loss-of-consciousness in humans

States of consciousness are likely mediated by multiple parallel yet interacting cortico-subcortical recurrent networks. Although the mesocircuit model has implicated the pallidocortical circuit as one such network, this circuit has not been extensively evaluated to identify network-level electrophysiological changes related to loss of consciousness (LOC). We characterize changes in the mesocircuit in awake versus propofol-induced LOC in humans by directly simultaneously recording from sensorimotor cortices (S1/M1) and globus pallidus interna and externa (GPi/GPe) in 12 patients with Parkinson disease undergoing deep brain stimulator implantation. Propofol-induced LOC is associated with increases in local power up to 20 Hz in GPi, 35 Hz in GPe, and 100 Hz in S1/M1. LOC is likewise marked by increased pallidocortical alpha synchrony across all nodes, with increased alpha/low beta Granger causal (GC) flow from GPe to all other nodes. In contrast, LOC is associated with decreased network-wide beta coupling and beta GC from M1 to the rest of the network. Results implicate an important and possibly central role of GPe in mediating LOC-related increases in alpha power, supporting a significant role of the GPe in modulating cortico-subcortical circuits for consciousness. Simultaneous LOC-related suppression of beta synchrony highlights that distinct oscillatory frequencies act independently, conveying unique network activity.

Subthalamic nucleus synchronization between beta band local field potential and single-unit activity in Parkinson's disease

Local field potential (LFP) oscillations in the beta band (13-30 Hz) in the subthalamic nucleus (STN) of Parkinson's disease patients have been implicated in disease severity and treatment response. The relationship between single-neuron activity in the STN and regional beta power changes remains unclear. We used spike-triggered average (STA) to assess beta synchronization in STN. Beta power and STA magnitude at the beta frequency range were compared in three conditions: STN versus other subcortical structures, dorsal versus ventral STN, and high versus low beta power STN recordings. Magnitude of STA-LFP was greater within the STN compared to extra-STN structures along the trajectory path, despite no difference in percentage of the total power. Within the STN, there was a higher percent beta power in dorsal compared to ventral STN but no difference in STA-LFP magnitude. Further refining the comparison to high versus low beta peak power recordings inside the STN to evaluate if single-unit activity synchronized more strongly with beta band activity in areas of high beta power resulted in a significantly higher STA magnitude for areas of high beta power. Overall, these results suggest that STN single units strongly synchronize to beta activity, particularly units in areas of high beta power.

Abnormally low sensorimotor α band nonlinearity serves as an effective EEG biomarker of Parkinson's disease

Biomarkers obtained from the neurophysiological signals of patients with Parkinson's disease (PD) have objective value in assessing their motor condition for effective diagnosis, monitoring, and clinical intervention. Prominent cortical biomarkers of PD have typically been derived from various β band wave features. This study approached the topic from an alternative perspective and attempted to estimate a recently suggested measure representing α band nonlinear autocorrelative memory from a publicly available EEG dataset that involves 15 patients with earlier-stage PD (dopaminergic medication OFF and ON states) and 16 age-matched healthy controls. The cortical nonlinearity was elevated for the PD ON state compared with the OFF state for bilateral sensorimotor channels C3 and C4 (n = 26; P = 0.003). A similar statistical difference was also identified between PD OFF state and healthy subjects (n = 26; P = 0.049). Analysis over all channels revealed that the α band nonlinearity induced upon medication was constrained to sensorimotor regions. The α nonlinearity measure was compared with a well-accepted cortical biomarker of β-γ phase-amplitude coupling (PAC). They were in moderate negative correlation (r = -0.412; P = 0.036) for only healthy subjects, but not for the patients. The nonlinearity measure was found to be insusceptible to the nonstationary variations within the particular data. Our study provides further evidence that the α band nonlinearity measure can serve as a promising cortical biomarker of PD. The suggested measure can be estimated from a noninvasive low-resolution single scalp EEG channel of patients with relatively early-stage PD, who did not yet need to undergo deep brain stimulation operation.NEW & NOTEWORTHY This study suggests a nonlinearity measure that differentiates Parkinson's disease (PD) dopamine OFF-state scalp EEG data from those of dopamine ON-state patients and healthy subjects. Unlike typical PD cortical biomarkers based on β band activity, this metric shows elevation upon dopaminergic medication in the α band. We provide evidence supporting its potential as an early-stage promising PD biomarker that can be estimated from noninvasive EEG recordings with low resolution and SNR.

Temporally non-regular patterns of deep brain stimulation (DBS) enhance assessment of evoked potentials while maintaining motor symptom management in Parkinson's disease (PD)

BACKGROUND

Traditional deep brain stimulation (DBS) at fixed regular frequencies (>100 Hz) is effective in treating motor symptoms of Parkinson's disease (PD). Temporally non-regular patterns of DBS are a new parameter space that may help increase efficacy and efficiency.

OBJECTIVE

To compare the effects of temporally non-regular patterns of DBS to traditional regularly-spaced pulses.

METHODS

We simultaneously recorded local field potentials (LFP) and monitored motor symptoms (tremor and bradykinesia) in persons with PD during DBS in subthalamic nucleus (STN). We quantified both oscillatory activity and DBS local evoked potentials (DLEPs) from the LFP.

RESULTS

Temporally non-regular patterns were as effective as traditional pulse patterns in modulating motor symptoms, oscillatory activity, and DLEPs. Moreover, one of our novel patterns enabled recording of longer duration DLEPs during clinically effective stimulation.

CONCLUSIONS

Stimulation gaps of 50 ms can be used to increase efficiency and to enable regular assessment of long-duration DLEPs while maintaining effective symptom management. This may be a promising paradigm for closed-loop DBS with biomarker assessment during the gaps.

Dystonia and Parkinson's disease: Do they have a shared biology?

Parkinsonism and dystonia co-occur across many movement disorders and are most encountered in the setting of Parkinson's disease. Here we aim to explore the shared neurobiological underpinnings of dystonia and parkinsonism through the clinical lens of the conditions in which these movement disorders can be seen together. Foregrounding the discussion, we briefly review the circuits of the motor system and the neuroanatomical and neurophysiological aspects of motor control and highlight their relevance to the proposed pathophysiology of parkinsonism and dystonia. Insight into shared biology is then sought from dystonia occurring in PD and other forms of parkinsonism including those disorders in which both can be co-expressed simultaneously. We organize these within a biological schema along with important questions to be addressed in this space.

Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation

Closed-loop adaptive deep brain stimulation (aDBS) can deliver individualized therapy at an unprecedented temporal precision for neurological disorders. This has the potential to lead to a breakthrough in neurotechnology, but the translation to clinical practice remains a significant challenge. Via bidirectional implantable brain-computer-interfaces that have become commercially available, aDBS can now sense and selectively modulate pathophysiological brain circuit activity. Pilot studies investigating different aDBS control strategies showed promising results, but the short experimental study designs have not yet supported individualized analyses of patient-specific factors in biomarker and therapeutic response dynamics. Notwithstanding the clear theoretical advantages of a patient-tailored approach, these new stimulation possibilities open a vast and mostly unexplored parameter space, leading to practical hurdles in the implementation and development of clinical trials. Therefore, a thorough understanding of the neurophysiological and neurotechnological aspects related to aDBS is crucial to develop evidence-based treatment regimens for clinical practice. Therapeutic success of aDBS will depend on the integrated development of strategies for feedback signal identification, artifact mitigation, signal processing, and control policy adjustment, for precise stimulation delivery tailored to individual patients. The present review introduces the reader to the neurophysiological foundation of aDBS for Parkinson's disease (PD) and other network disorders, explains currently available aDBS control policies, and highlights practical pitfalls and difficulties to be addressed in the upcoming years. Finally, it highlights the importance of interdisciplinary clinical neurotechnological research within and across DBS centers, toward an individualized patient-centered approach to invasive brain stimulation. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Bradykinesia and Its Progression Are Related to Interhemispheric Beta Coherence

OBJECTIVE

Bradykinesia is the major cardinal motor sign of Parkinson disease (PD), but its neural underpinnings are unclear. The goal of this study was to examine whether changes in bradykinesia following long-term subthalamic nucleus (STN) deep brain stimulation (DBS) are linked to local STN beta (13-30 Hz) dynamics or a wider bilateral network dysfunction.

METHODS

Twenty-one individuals with PD implanted with sensing neurostimulators (Activa® PC + S, Medtronic, PLC) in the STN participated in a longitudinal 'washout' therapy study every three to 6 months for an average of 3 years. At each visit, participants were withdrawn from medication (12/24/48 hours) and had DBS turned off (>60 minutes) before completing a repetitive wrist-flexion extension task, a validated quantitative assessment of bradykinesia, while local field potentials were recorded. Local STN beta dynamics were investigated via beta power and burst duration, while interhemispheric beta synchrony was assessed with STN-STN beta coherence.

RESULTS

Higher interhemispheric STN beta coherence, but not contralateral beta power or burst duration, was significantly associated with worse bradykinesia. Bradykinesia worsened off therapy over time. Interhemispheric STN-STN beta coherence also increased over time, whereas beta power and burst duration remained stable. The observed change in bradykinesia was related to the change in interhemispheric beta coherence, with greater increases in synchrony associated with further worsening of bradykinesia.

INTERPRETATION

Together, these findings implicate interhemispheric beta synchrony as a neural correlate of the progression of bradykinesia following chronic STN DBS. This could imply the existence of a pathological bilateral network contributing to bradykinesia in PD. ANN NEUROL 2023;93:1029-1039.

TMS Bursts Can Modulate Local and Networks Oscillations During Lower-Limb Movement

PURPOSE

Lower-limb motor functions involve processing information via both motor and cognitive control networks. Measuring oscillations is a key element in communication within and between cortical networks during high-order motor functions. Increased midfrontal theta oscillations are related to improved lower-limb motor performances in patients with movement disorders. Noninvasive neuromodulation approaches have not been explored extensively to understand the oscillatory mechanism of lower-limb motor functions. This study aims to examine the effects of repetitive transcranial magnetic stimulation on local and network EEG oscillations in healthy elderly subjects.

METHODS

Eleven healthy elderly subjects (67-73 years) were recruited via advertisements, and they underwent both active and sham stimulation procedures in a random, counterbalanced design. Transcranial magnetic stimulation bursts (θ-transcranial magnetic stimulation; 4 pulses/second) were applied over the midfrontal lead (vertex) before a GO-Cue pedaling task, and signals were analyzed using time-frequency methods.

RESULTS

Transcranial magnetic stimulation bursts increase the theta activity in the local ( p = 0.02) and the associated network during the lower-limb pedaling task ( p = 0.02). Furthermore, after task-related transcranial magnetic stimulation burst sessions, increased resting-state alpha activity was observed in the midfrontal region ( p = 0.01).

CONCLUSIONS

This study suggests the ability of midfrontal transcranial magnetic stimulation bursts to directly modulate local and network oscillations in a frequency manner during lower-limb motor task. Transcranial magnetic stimulation burst-induced modulation may provide insights into the functional roles of oscillatory activity during lower-limb movement in normal and disease conditions.

The effect of deep brain stimulation in Parkinson's disease reflected in EEG microstates

Mechanisms of deep brain stimulation (DBS) on cortical networks were explored mainly by fMRI. Advanced analysis of high-density EEG is a source of additional information and may provide clinically useful biomarkers. The presented study evaluates EEG microstates in Parkinson's disease and the effect of DBS of the subthalamic nucleus (STN). The association between revealed spatiotemporal dynamics of brain networks and changes in oscillatory activity and clinical examination were assessed. Thirty-seven patients with Parkinson's disease treated by STN-DBS underwent two sessions (OFF and ON stimulation conditions) of resting-state EEG. EEG microstates were analyzed in patient recordings and in a matched healthy control dataset. Microstate parameters were then compared across groups and were correlated with clinical and neuropsychological scores. Of the five revealed microstates, two differed between Parkinson's disease patients and healthy controls. Another microstate differed between ON and OFF stimulation conditions in the patient group and restored parameters in the ON stimulation state toward to healthy values. The mean beta power of that microstate was the highest in patients during the OFF stimulation condition and the lowest in healthy controls; sources were localized mainly in the supplementary motor area. Changes in microstate parameters correlated with UPDRS and neuropsychological scores. Disease specific alterations in the spatiotemporal dynamics of large-scale brain networks can be described by EEG microstates. The approach can reveal changes reflecting the effect of DBS on PD motor symptoms as well as changes probably related to non-motor symptoms not influenced by DBS.

Neural pathway connectivity and discharge changes between M1 and STN in hemiparkinsonian rats

Alterations of electrophysiological activities, such as changed spike firing rates, reshaping the firing patterns, and aberrant frequency oscillations between the subthalamic nucleus (STN) and the primary motor cortex (M1), are thought to contribute to motor impairment in Parkinson's disease (PD). However, the alterations of electrophysiological characteristics of STN and M1 in PD are still unclear, especially under specific treadmill movement. To examine the relationship between electrophysiological activity in the STN-M1 pathway, extracellular spike trains and local field potential (LFPs) of STN and M1 were simultaneously recorded during resting and movement in unilateral 6-hydroxydopamine (6-OHDA) lesioned rats. The results showed that the identified STN neurons and M1 neurons exhibited abnormal neuronal activity after dopamine loss. The dopamine depletion altered the LFP power in STN and M1 whatever in rest or movement states. Furthermore, the enhanced synchronization of LFP oscillations after dopamine loss was found in 12-35 Hz (beta frequencies) between the STN and M1 during rest and movement. In addition, STN neurons were phase-locked firing to M1 oscillations at 12-35 Hz during rest epochs in 6-OHDA lesioned rats. The dopamine depletion also impaired the anatomical connectivity between the M1 and STN by injecting anterograde neuroanatomical tracing virus into M1 in control and PD rats. Collectively, impairment of' electrophysiological activity and anatomical connectivity in the M1-STN pathway may be the basis for dysfunction of the cortico-basal ganglia circuit, correlating with motor symptoms of PD.

Evoked resonant neural activity in subthalamic local field potentials reflects basal ganglia network dynamics

Evoked resonant neural activity (ERNA) is induced by subthalamic deep brain stimulation (DBS) and was recently suggested as a marker of lead placement and contact selection in Parkinson's disease. Yet, its underlying mechanisms and how it is modulated by stimulation parameters are unclear. Here, we recorded local field potentials from 27 Parkinson's disease patients, while leads were externalised to scrutinise the ERNA. First, we show that ERNA in the time series waveform and spectrogram likely represent the same activity, which was contested before. Second, our results show that the ERNA has fast and slow dynamics during stimulation, consistent with the synaptic failure hypothesis. Third, we show that ERNA parameters are modulated by different DBS frequencies, intensities, medication states and stimulation modes (continuous DBS vs. adaptive DBS). These results suggest the ERNA might prove useful as a predictor of the best DBS frequency and lowest effective intensity in addition to contact selection. Changes with levodopa and DBS mode suggest that the ERNA may indicate the state of the cortico-basal ganglia circuit making it a putative biomarker to track clinical state in adaptive DBS.

The aperiodic exponent of subthalamic field potentials reflects excitation/inhibition balance in Parkinsonism

Periodic features of neural time-series data, such as local field potentials (LFPs), are often quantified using power spectra. While the aperiodic exponent of spectra is typically disregarded, it is nevertheless modulated in a physiologically relevant manner and was recently hypothesised to reflect excitation/inhibition (E/I) balance in neuronal populations. Here, we used a cross-species in vivo electrophysiological approach to test the E/I hypothesis in the context of experimental and idiopathic Parkinsonism. We demonstrate in dopamine-depleted rats that aperiodic exponents and power at 30-100 Hz in subthalamic nucleus (STN) LFPs reflect defined changes in basal ganglia network activity; higher aperiodic exponents tally with lower levels of STN neuron firing and a balance tipped towards inhibition. Using STN-LFPs recorded from awake Parkinson's patients, we show that higher exponents accompany dopaminergic medication and deep brain stimulation (DBS) of STN, consistent with untreated Parkinson's manifesting as reduced inhibition and hyperactivity of STN. These results suggest that the aperiodic exponent of STN-LFPs in Parkinsonism reflects E/I balance and might be a candidate biomarker for adaptive DBS.

The Effects of Subthalamic Nucleus Deep Brain Stimulation and Retention Delay on Memory-Guided Reaching Performance in People with Parkinson's Disease

BACKGROUND

Subthalamic nucleus deep brain stimulation (STN-DBS) improves intensive aspects of movement (velocity) in people with Parkinson's disease (PD) but impairs the more cognitively demanding coordinative aspects of movement (error). We extended these findings by evaluating STN-DBS induced changes in intensive and coordinative aspects of movement during a memory-guided reaching task with varying retention delays.

OBJECTIVE

We evaluated the effect of STN-DBS on motor control during a memory-guided reaching task with short and long retention delays in participants with PD and compared performance to healthy controls (HC).

METHODS

Eleven participants with PD completed the motor section of the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS III) and performed a memory-guided reaching task under four different STN-DBS conditions (DBS-OFF, DBS-RIGHT, DBS-LEFT, and DBS-BOTH) and two retention delays (0.5 s and 5 s). An additional 13 HC completed the memory-guided reaching task.

RESULTS

Unilateral and bilateral STN-DBS improved the MDS-UPDRS III scores. In the memory-guided reaching task, both unilateral and bilateral STN-DBS increased the intensive aspects of movement (amplitude and velocity) in the direction toward HC but impaired coordinative aspects of movement (error) away from the HC. Furthermore, movement time was decreased but reaction time was unaffected by STN-DBS. Shorter retention delays increased amplitude and velocity, decreased movement times, and decreased error, but increased reaction times in the participants with PD. There were no interactions between STN-DBS condition and retention delay.

CONCLUSION

STN-DBS may affect cognitive-motor functioning by altering activity throughout cortico-basal ganglia networks and the oscillatory activity subserving them.

A population-normalized tractographic fiber atlas of the anterior limb of the internal capsule: relevance to surgical neuromodulation

OBJECTIVE

The anterior limb of the internal capsule (ALIC) is a white matter highway that connects several subcortical structures to the prefrontal cortex. Although surgical interventions in the ALIC have been used to treat a number of psychiatric illnesses, there is significant debate regarding what fibers are targeted for intervention. This debate is partially due to an incomplete understanding of connectivity in the region.

METHODS

To better understand this complex structure, the authors employed a novel tractography-based approach to examine how fibers from the thalamus and subthalamic nucleus (STN) traverse the ALIC. Furthermore, the authors analyzed connections from the medial dorsal nucleus, anterior nucleus, and ventral anterior nucleus of the thalamus.

RESULTS

The results showed that there is an organizational gradient of thalamic fibers medially and STN fibers laterally in the ALIC that fades more anteriorly. These findings, in combination with the known corticotopic organization described by previous studies, allow for a more thorough understanding of the organization of the white matter fibers in the ALIC.

CONCLUSIONS

These results are important for understanding and targeting of neuromodulatory therapies in the ALIC and may help explain why differences in therapeutic effect are observed for different areas of the ALIC.

Subthalamic high-beta oscillation informs the outcome of deep brain stimulation in patients with Parkinson's disease

Background

The therapeutic effect of deep brain stimulation (DBS) of the subthalamic nucleus (STN) for Parkinson's disease (PD) is related to the modulation of pathological neural activities, particularly the synchronization in the β band (13–35 Hz). However, whether the local β activity in the STN region can directly predict the stimulation outcome remains unclear.

Objective

We tested the hypothesis that low-β (13–20 Hz) and/or high-β (20–35 Hz) band activities recorded from the STN region can predict DBS efficacy.

Methods

Local field potentials (LFPs) were recorded in 26 patients undergoing deep brain stimulation surgery in the subthalamic nucleus area. Recordings were made after the implantation of the DBS electrode prior to its connection to a stimulator. The maximum normalized powers in the theta (4–7 Hz), alpha (7–13 Hz), low-β (13–20 Hz), high-β (20–35 Hz), and low-γ (40–55 Hz) subbands in the postoperatively recorded LFP were correlated with the stimulation-induced improvement in contralateral tremor or bradykinesia–rigidity. The distance between the contact selected for stimulation and the contact with the maximum subband power was correlated with the stimulation efficacy. Following the identification of the potential predictors by the significant correlations, a multiple regression analysis was performed to evaluate their effect on the outcome.

Results

The maximum high-β power was positively correlated with bradykinesia–rigidity improvement (rs = 0.549, p < 0.0001). The distance to the contact with maximum high-β power was negatively correlated with bradykinesia–rigidity improvement (rs = −0.452, p < 0.001). No significant correlation was observed with low-β power. The maximum high-β power and the distance to the contact with maximum high-β power were both significant predictors for bradykinesia–rigidity improvement in the multiple regression analysis, explaining 37.4% of the variance altogether. Tremor improvement was not significantly correlated with any frequency.

Conclusion

High-β oscillations, but not low-β oscillations, recorded from the STN region with the DBS lead can inform stimulation-induced improvement in contralateral bradykinesia–rigidity in patients with PD. High-β oscillations can help refine electrode targeting and inform contact selection for DBS therapy.

Single-neuron bursts encode pathological oscillations in subcortical nuclei of patients with Parkinson's disease and essential tremor

Deep brain stimulation procedures offer an invaluable opportunity to study disease through intracranial recordings from awake patients. Here, we address the relationship between single-neuron and aggregate-level (local field potential; LFP) activities in the subthalamic nucleus (STN) and thalamic ventral intermediate nucleus (Vim) of patients with Parkinson's disease (n = 19) and essential tremor (n = 16), respectively. Both disorders have been characterized by pathologically elevated LFP oscillations, as well as an increased tendency for neuronal bursting. Our findings suggest that periodic single-neuron bursts encode both pathophysiological beta (13 to 33 Hz; STN) and tremor (4 to 10 Hz; Vim) LFP oscillations, evidenced by strong time-frequency and phase-coupling relationships between the bursting and LFP signals. Spiking activity occurring outside of bursts had no relationship to the LFP. In STN, bursting activity most commonly preceded the LFP oscillation, suggesting that neuronal bursting generated within STN may give rise to an aggregate-level LFP oscillation. In Vim, LFP oscillations most commonly preceded bursting activity, suggesting that neuronal firing may be entrained by periodic afferent inputs. In both STN and Vim, the phase-coupling relationship between LFP and high-frequency oscillation (HFO) signals closely resembled the relationships between the LFP and single-neuron bursting. This suggests that periodic single-neuron bursting is likely representative of a higher spatial and temporal resolution readout of periodic increases in the amplitude of HFOs, which themselves may be a higher resolution readout of aggregate-level LFP oscillations. Overall, our results may reconcile "rate" and "oscillation" models of Parkinson's disease and shed light on the single-neuron basis and origin of pathophysiological oscillations in movement disorders.

Cortical beta burst dynamics are altered in Parkinson's disease but normalized by deep brain stimulation

Exaggerated subthalamic beta oscillatory activity and increased beta range cortico-subthalamic synchrony have crystallized as the electrophysiological hallmarks of Parkinson's disease. Beta oscillatory activity is not tonic but occurs in 'bursts' of transient amplitude increases. In Parkinson's disease, the characteristics of these bursts are altered especially in the basal ganglia. However, beta oscillatory dynamics at the cortical level and how they compare with healthy brain activity is less well studied. We used magnetoencephalography (MEG) to study sensorimotor cortical beta bursting and its modulation by subthalamic deep brain stimulation in Parkinson's disease patients and age-matched healthy controls. We show that the changes in beta bursting amplitude and duration typical of Parkinson's disease can also be observed in the sensorimotor cortex, and that they are modulated by chronic subthalamic deep brain stimulation, which, in turn, is reflected in improved motor function at the behavioural level. In addition to the changes in individual beta bursts, their timing relative to each other was altered in patients compared to controls: bursts were more clustered in untreated Parkinson's disease, occurring in 'bursts of bursts', and re-burst probability was higher for longer compared to shorter bursts. During active deep brain stimulation, the beta bursting in patients resembled healthy controls' data. In summary, both individual bursts' characteristics and burst patterning are affected in Parkinson's disease, and subthalamic deep brain stimulation normalizes some of these changes to resemble healthy controls' beta bursting activity, suggesting a non-invasive biomarker for patient and treatment follow-up.

Spectral and spatial distribution of subthalamic beta peak activity in Parkinson's disease patients

Current efforts to optimize subthalamic deep brain stimulation in Parkinson's disease patients aim to harness local oscillatory activity in the beta frequency range (13-35 Hz) as a feedback-signal for demand-based adaptive stimulation paradigms. A high prevalence of beta peak activity is prerequisite for this approach to become routine clinical practice. In a large dataset of postoperative rest recordings from 106 patients we quantified occurrence and identified determinants of spectral peaks in the alpha, low and high beta bands. At least one peak in beta band occurred in 92% of patients and 84% of hemispheres off medication, irrespective of demographic parameters, clinical subtype or motor symptom severity. Distance to previously described clinical sweet spot was significantly related both to beta peak occurrence and to spectral power (rho -0.21, p 0.006), particularly in the high beta band. Electrophysiological landscapes of our cohort's dataset in normalised space showed divergent heatmaps for alpha and beta but found similar regions for low and high beta frequency bands. We discuss potential ramifications for clinicians' programming decisions. In summary, this report provides robust evidence that spectral peaks in beta frequency range can be detected in the vast majority of Parkinsonian subthalamic nuclei, increasing confidence in the broad applicability of beta-guided deep brain stimulation.

Somatotopic Organization of Hyperdirect Pathway Projections From the Primary Motor Cortex in the Human Brain

Background

The subthalamic nucleus (STN) is an effective neurosurgical target to improve motor symptoms in Parkinson's Disease (PD) patients. MR-guided Focused Ultrasound (MRgFUS) subthalamotomy is being explored as a therapeutic alternative to Deep Brain Stimulation (DBS) of the STN. The hyperdirect pathway provides a direct connection between the cortex and the STN and is likely to play a key role in the therapeutic effects of MRgFUS intervention in PD patients.

Objective

This study aims to investigate the topography and somatotopy of hyperdirect pathway projections from the primary motor cortex (M1).

Methods

We used advanced multi-fiber tractography and high-resolution diffusion MRI data acquired on five subjects of the Human Connectome Project (HCP) to reconstruct hyperdirect pathway projections from M1. Two neuroanatomy experts reviewed the anatomical accuracy of the tracts. We extracted the fascicles arising from the trunk, arm, hand, face and tongue area from the reconstructed pathways. We assessed the variability among subjects based on the fractional anisotropy (FA) and mean diffusivity (MD) of the fibers. We evaluated the spatial arrangement of the different fascicles using the Dice Similarity Coefficient (DSC) of spatial overlap and the centroids of the bundles.

Results

We successfully reconstructed hyperdirect pathway projections from M1 in all five subjects. The tracts were in agreement with the expected anatomy. We identified hyperdirect pathway fascicles projecting from the trunk, arm, hand, face and tongue area in all subjects. Tract-derived measurements showed low variability among subjects, and similar distributions of FA and MD values among the fascicles projecting from different M1 areas. We found an anterolateral somatotopic arrangement of the fascicles in the corona radiata, and an average overlap of 0.63 in the internal capsule and 0.65 in the zona incerta.

Conclusion

Multi-fiber tractography combined with high-resolution diffusion MRI data enables the identification of the somatotopic organization of the hyperdirect pathway. Our preliminary results suggest that the subdivisions of the hyperdirect pathway projecting from the trunk, arm, hand, face, and tongue motor area are intermixed at the level of the zona incerta and posterior limb of the internal capsule, with a predominantly overlapping topographical organization in both regions. Subject-specific knowledge of the hyperdirect pathway somatotopy could help optimize target definition in MRgFUS intervention.

Subthalamic deep brain stimulation of an anatomically detailed model of the human hyperdirect pathway

The motor hyperdirect pathway (HDP) is considered a key target in the treatment of Parkinson's disease with subthalamic deep brain stimulation (DBS). This hypothesis is partially derived from the association of HDP activation with evoked potentials (EPs) generated in the motor cortex and subthalamic nucleus (STN) after a DBS pulse. However, the biophysical details of how and when DBS-induced action potentials (APs) in HDP neurons reach their terminations in the cortex or STN remain unclear. Therefore, we used an anatomically detailed representation of the motor HDP, as well as the internal capsule (IC), in a model of human subthalamic DBS to explore AP activation and transmission in the HDP and IC. Our results show that small diameter HDP axons exhibited AP initiation in their subthalamic terminal arbor, which resulted in relatively long transmission latencies to cortex (∼3.5-8 ms). Alternatively, large diameter HDP axons were most likely to be directly activated in the capsular region, which resulted in short transmission times to the cortex (∼1-3 ms). However, those large diameter HDP antidromic APs would be indistinguishable from any other IC axons that were also activated by the stimulus. Conversely, DBS-induced APs in both small and large diameter HDP axons reached their synaptic boutons in the STN with similar timings, but both spanned a wide temporal range (∼0.5-5 ms). We also found that using anodic or bipolar stimulation helped to bias activation of the HDP over the IC. These computational results provide useful information for linking HDP activation with EP recordings in clinical experiments.NEW & NOTEWORTHY We used biophysical models to study pathway recruitment and conduction latencies of the hyperdirect pathway (HDP) in response to subthalamic deep brain stimulation (DBS). The model system allowed us to assess the influence of increased anatomical realism on pathway activity and the possibility of identifying HDP activity in evoked potentials (EPs) recorded in either the subthalamic nucleus (STN) or cortex. The model predicts that HDP activation is accentuated by complex axonal branching in the STN.

Dopaminergic Modulation of Local Non-oscillatory Activity and Global-Network Properties in Parkinson's Disease: An EEG Study

Dopaminergic medication for Parkinson's disease (PD) modulates neuronal oscillations and functional connectivity (FC) across the basal ganglia-thalamic-cortical circuit. However, the non-oscillatory component of the neuronal activity, potentially indicating a state of excitation/inhibition balance, has not yet been investigated and previous studies have shown inconsistent changes of cortico-cortical connectivity as a response to dopaminergic medication. To further elucidate changes of regional non-oscillatory component of the neuronal power spectra, FC, and to determine which aspects of network organization obtained with graph theory respond to dopaminergic medication, we analyzed a resting-state electroencephalography (EEG) dataset including 15 PD patients during OFF and ON medication conditions. We found that the spectral slope, typically used to quantify the broadband non-oscillatory component of power spectra, steepened particularly in the left central region in the ON compared to OFF condition. In addition, using lagged coherence as a FC measure, we found that the FC in the beta frequency range between centro-parietal and frontal regions was enhanced in the ON compared to the OFF condition. After applying graph theory analysis, we observed that at the lower level of topology the node degree was increased, particularly in the centro-parietal area. Yet, results showed no significant difference in global topological organization between the two conditions: either in global efficiency or clustering coefficient for measuring global and local integration, respectively. Interestingly, we found a close association between local/global spectral slope and functional network global efficiency in the OFF condition, suggesting a crucial role of local non-oscillatory dynamics in forming the functional global integration which characterizes PD. These results provide further evidence and a more complete picture for the engagement of multiple cortical regions at various levels in response to dopaminergic medication in PD.

Subthalamic Beta Activity in Parkinson's Disease May Be Linked to Dorsal Striatum Gray Matter Volume and Prefrontal Cortical Thickness: A Pilot Study

Background

Excessive oscillations at beta frequencies (13–35 Hz) in the subthalamic nucleus (STN) represent a pathophysiological hallmark of Parkinson's disease (PD), which correlates well with parkinsonian symptoms and is reduced in response to standard disease treatments. However, the association of disease-specific regional gray matter (GM) atrophy or cortical thickness (CT) with the presence of STN beta oscillatory activity has been poorly investigated but is of relevance given the potential of these variables for extracting information about PD pathophysiology. This exploratory study investigated the involvement of regional GM volume and CT in the basal ganglia-cortical network and its potential association with the presence of STN beta oscillatory activity in PD.

Methods

We acquired preoperative GM densities on T1-weighted magnetic resonance imaging scans and we carried out regional estimation of GM volume and CT. LFP activities from the STN were recorded post-operatively in 7 cognitively preserved PD patients off dopaminergic medication undergoing deep-brain stimulation surgery. Oscillatory beta power was determined by power spectral density of 4-min resting state STN LFP activity. Spearman partial correlations and regression analysis were used to screen the presence of STN beta power for their relationship with GM volume and CT measurements.

Results

After controlling for the effects of age, educational level, and disease duration, and after correcting for multiple testing, enhanced STN beta power showed significant and negative correlations between, first, volume of the right putamen and left caudate nucleus, and second, smaller CT in frontal regions involving the left rostral middle frontal gyrus (MFG) and left medial orbitofrontal gyrus. A lower volume in the right putamen and a lower CT in the left MFG demonstrated the strongest associations with increased STN beta power.

Conclusions

These tentative results seem to suggest that STN LFP beta frequencies may be mainly linked to different but ongoing parallel neurodegenerative processes, on the one hand, to GM volume reduction in dorsal striatum, and on the other hand, to CT reduction of prefrontal-“associative” regions. These findings could further delineate the brain structural interactions underpinning the exaggerated STN beta activity commonly observed in PD patients.

Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S

Deep Brain Stimulation (DBS) is an important tool in the treatment of pharmacologically resistant neurological movement disorders such as essential tremor (ET) and Parkinson's disease (PD). However, the open-loop design of current systems may be holding back the true potential of invasive neuromodulation. In the last decade we have seen an explosion of activity in the use of feedback to "close the loop" on neuromodulation in the form of adaptive DBS (aDBS) systems that can respond to the patient's therapeutic needs. In this paper we summarize the accomplishments of a 5-year study at the University of Washington in the use of neural feedback from an electrocorticography strip placed over the sensorimotor cortex. We document our progress from an initial proof of hardware all the way to a fully implanted adaptive stimulation system that leverages machine-learning approaches to simplify the programming process. In certain cases, our systems out-performed current open-loop approaches in both power consumption and symptom suppression. Throughout this effort, we collaborated with neuroethicists to capture patient experiences and take them into account whilst developing ethical aDBS approaches. Based on our results we identify several key areas for future work. "Graded" aDBS will allow the system to smoothly tune the stimulation level to symptom severity, and frequent automatic calibration of the algorithm will allow aDBS to adapt to the time-varying dynamics of the disease without additional input from a clinician. Additionally, robust computational models of the pathophysiology of ET will allow stimulation to be optimized to the nuances of an individual patient's symptoms. We also outline the unique advantages of using cortical electrodes for control and the remaining hardware limitations that need to be overcome to facilitate further development in this field. Over the course of this study we have verified the potential of fully-implanted, cortically driven aDBS as a feasibly translatable treatment for pharmacologically resistant ET.

Subthalamic burst firing: A pathophysiological target in Parkinson's disease

Understanding the pathophysiological mechanism of Parkinson's disease (PD) in the subthalamic nucleus (STN) has become a critical issue since deep brain stimulation (DBS) in this region has been proven as an effective treatment for this disease. The STN possesses a special ability to switch from the spike to the burst firing mode in response to dopamine deficiency in parkinsonism, and this STN burst is considered an electrophysiological signature of the cortico-basal ganglia circuit in the brains of PD patients. This review focuses on the role of STN burst firing in the pathophysiology of PD and during DBS. Here, we review existing literature on how STN bursts originate and the specific factors affecting their formation; how STN burst firing causes motor symptoms in PD and how interventions can rescue these symptoms. Finally, the similarities and differences between the two electrophysiological hallmarks of PD, STN burst firing and beta-oscillation, are discussed. STN burst firing should be considered as a pathophysiological target in PD during treatment with DBS.

Adaptive, personalized closed-loop therapy for Parkinson's disease: biochemical, neurophysiological, and wearable sensing systems

INTRODUCTION

Motor complication management is one of the main unmet needs in Parkinson's disease patients.

AREAS COVERED

Among the most promising emerging approaches for handling motor complications in Parkinson's disease, adaptive deep brain stimulation strategies operating in closed-loop have emerged as pivotal to deliver sustained, near-to-physiological inputs to dysfunctional basal ganglia-cortical circuits over time. Existing sensing systems that can provide feedback signals to close the loop include biochemical-, neurophysiological- or wearable-sensors. Biochemical sensing allows to directly monitor the pharmacokinetic and pharmacodynamic of antiparkinsonian drugs and metabolites. Neurophysiological sensing relies on neurotechnologies to sense cortical or subcortical brain activity and extract real-time correlates of symptom intensity or symptom control during DBS. A more direct representation of the symptom state, particularly the phenomenological differentiation and quantification of motor symptoms, can be realized via wearable sensor technology.

EXPERT OPINION

Biochemical, neurophysiologic, and wearable-based biomarkers are promising technological tools that either individually or in combination could guide adaptive therapy for Parkinson's disease motor symptoms in the future.

Differential Effects of Pathological Beta Burst Dynamics Between Parkinson's Disease Phenotypes Across Different Movements

Background: Resting state beta band (13-30 Hz) oscillations represent pathological neural activity in Parkinson's disease (PD). It is unknown how the peak frequency or dynamics of beta oscillations may change among fine, limb, and axial movements and different disease phenotypes. This will be critical for the development of personalized closed loop deep brain stimulation (DBS) algorithms during different activity states. Methods: Subthalamic (STN) and local field potentials (LFPs) were recorded from a sensing neurostimulator (Activa® PC + S, Medtronic PLC.) in fourteen PD participants (six tremor-dominant and eight akinetic-rigid) off medication/off STN DBS during 30 s of repetitive alternating finger tapping, wrist-flexion extension, stepping in place, and free walking. Beta power peaks and beta burst dynamics were identified by custom algorithms and were compared among movement tasks and between tremor-dominant and akinetic-rigid groups. Results: Beta power peaks were evident during fine, limb, and axial movements in 98% of movement trials; the peak frequencies were similar during each type of movement. Burst power and duration were significantly larger in the high beta band, but not in the low beta band, in the akinetic-rigid group compared to the tremor-dominant group. Conclusion: The conservation of beta peak frequency during different activity states supports the feasibility of patient-specific closed loop DBS algorithms driven by the dynamics of the same beta band during different activities. Akinetic-rigid participants had greater power and longer burst durations in the high beta band than tremor-dominant participants during movement, which may relate to the difference in underlying pathophysiology between phenotypes.

Frequency-specific network activity predicts bradykinesia severity in Parkinson's disease

OBJECTIVE

Bradykinesia has been associated with beta and gamma band interactions in the basal ganglia-thalamo-cortical circuit in Parkinson's disease. In this present cross-sectional study, we aimed to search for neural networks with electroencephalography whose frequency-specific actions may predict bradykinesia.

METHODS

Twenty Parkinsonian patients treated with bilateral subthalamic stimulation were first prescreened while we selected four levels of contralateral stimulation (0: OFF, 1-3: decreasing symptoms to ON state) individually, based on kinematics. In the screening period, we performed 64-channel electroencephalography measurements simultaneously with electromyography and motion detection during a resting state, finger tapping, hand grasping tasks, and pronation-supination of the arm, with the four levels of contralateral stimulation. We analyzed spectral power at the low (13-20 Hz) and high (21-30 Hz) beta frequency bands and low (31-60 Hz) and high (61-100 Hz) gamma frequency bands using the dynamic imaging of coherent sources. Structural equation modelling estimated causal relationships between the slope of changes in network beta and gamma activities and the slope of changes in bradykinesia measures.

RESULTS

Activity in different subnetworks, including predominantly the primary motor and premotor cortex, the subthalamic nucleus predicted the slopes in amplitude and speed while switching between stimulation levels. These subnetwork dynamics on their preferred frequencies predicted distinct types and parameters of the movement only on the contralateral side.

DISCUSSION

Concurrent subnetworks affected in bradykinesia and their activity changes in the different frequency bands are specific to the type and parameters of the movement; and the primary motor and premotor cortex are common nodes.

Lack of progression of beta dynamics after long-term subthalamic neurostimulation

OBJECTIVE

To investigate the progression of neural and motor features of Parkinson's disease in a longitudinal study, after washout of medication and bilateral subthalamic nucleus deep brain stimulation (STN DBS).

METHODS

Participants with clinically established Parkinson's disease underwent bilateral implantation of DBS leads (18 participants, 13 male) within the STN using standard functional frameless stereotactic technique and multi-pass microelectrode recording. Both DBS leads were connected to an implanted investigative sensing neurostimulator (Activa™ PC + S, Medtronic, PLC). Resting state STN local field potentials (LFPs) were recorded and motor disability, (the Movement Disorder Society-Unified Parkinson's Disease Rating Scale - motor subscale, MDS-UPDRS III) was assessed off therapy at initial programming, and after 6 months, 1 year, and yearly out to 5 years of treatment. The primary endpoint was measured at 3 years. At each visit, medication had been held for over 12/24 h and DBS was turned off for at least 60 min, by which time LFP spectra reached a steady state.

RESULTS

After 3 years of chronic DBS, there were no increases in STN beta band dynamics (p = 0.98) but there were increases in alpha band dynamics (p = 0.0027, 25 STNs). Similar results were observed in a smaller cohort out to 5 years. There was no increase in the MDS-UPDRS III score.

INTERPRETATION

These findings provide evidence that the beta oscillopathy does not substantially progress following combined STN DBS plus medication in moderate to advanced Parkinson's disease.

Peaks in the beta band of the human subthalamic nucleus: a case for low beta and high beta activity

OBJECTIVE

Peaks in the beta band of local field potentials (LFPs) may serve as a biological feedback signal for closed-loop deep brain stimulation (DBS) in Parkinson's disease (PD). However, the specific frequency of such peaks and their response to DBS and to different types of movement remains uncertain. In the present study, the authors examined the abundance of discernible peaks in the beta band and the effect of different types of movement and DBS on these peaks.

METHODS

Subthalamic nucleus LFPs were analyzed from 38 patients with PD in a frequency range between 10 and 35 Hz, as well as the impact of movement (gait, hand movements) and electrical stimulation on these peaks. The position of the electrode segments from which LFPs were recorded was computed.

RESULTS

The authors found a bimodal distribution of peaks in the beta band with discernible high- (27 Hz) and low-frequency (15 Hz) peaks. Movement of either hand had no significant effect on these peaks, whereas walking significantly reduced high-frequency beta peaks but not the peaks in the low beta band. Stimulation caused an amplitude-dependent suppression of both peaks.

CONCLUSIONS

DBS suppresses LFP beta peaks of different frequencies, whereas beta suppression caused by movement is dependent on the type of movement and frequency of the peak. These results will support the investigation of distinct LFP spectra for the application of closed-loop DBS.

Neural signatures of hyperdirect pathway activity in Parkinson's disease

Parkinson's disease (PD) is characterised by the emergence of beta frequency oscillatory synchronisation across the cortico-basal-ganglia circuit. The relationship between the anatomy of this circuit and oscillatory synchronisation within it remains unclear. We address this by combining recordings from human subthalamic nucleus (STN) and internal globus pallidus (GPi) with magnetoencephalography, tractography and computational modelling. Coherence between supplementary motor area and STN within the high (21-30 Hz) but not low (13-21 Hz) beta frequency range correlated with 'hyperdirect pathway' fibre densities between these structures. Furthermore, supplementary motor area activity drove STN activity selectively at high beta frequencies suggesting that high beta frequencies propagate from the cortex to the basal ganglia via the hyperdirect pathway. Computational modelling revealed that exaggerated high beta hyperdirect pathway activity can provoke the generation of widespread pathological synchrony at lower beta frequencies. These findings suggest a spectral signature and a pathophysiological role for the hyperdirect pathway in PD.

Development of CVN424: A Selective and Novel GPR6 Inverse Agonist Effective in Models of Parkinson Disease

GPR6 is an orphan G-protein-coupled receptor that has enriched expression in the striatopallidal, indirect pathway and medium spiny neurons of the striatum. This pathway is greatly impacted by the loss of the nigro-striatal dopaminergic neurons in Parkinson disease, and modulating this neurocircuitry can be therapeutically beneficial. In this study, we describe the in vitro and in vivo pharmacological characterization of (R)-1-(2-(4-(2,4-difluorophenoxy)piperidin-1-yl)-3-((tetrahydrofuran-3-yl)amino)-7,8-dihydropyrido[3,4-b]pyrazin-6(5H)-yl)ethan-1-one (CVN424), a highly potent and selective small-molecule inverse agonist for GPR6 that is currently undergoing clinical evaluation. CVN424 is brain-penetrant and shows dose-dependent receptor occupancy that attained brain 50% of receptor occupancy at plasma concentrations of 6.0 and 7.4 ng/ml in mice and rats, respectively. Oral administration of CVN424 dose-dependently increases locomotor activity and reverses haloperidol-induced catalepsy. Furthermore, CVN424 restored mobility in bilateral 6-hydroxydopamine lesion model of Parkinson disease. The presence and localization of GPR6 in medium spiny neurons of striatum postmortem samples from both nondemented control and patients with Parkinson disease were confirmed at the level of both RNA (using Nuclear Enriched Transcript Sort sequencing) and protein. This body of work demonstrates that CVN424 is a potent, orally active, and brain-penetrant GPR6 inverse agonist that is effective in preclinical models and is a potential therapeutic for improving motor function in patients with Parkinson disease. SIGNIFICANCE STATEMENT: CVN424 represents a nondopaminergic novel drug for potential use in patients with Parkinson disease.

Predicting optimal deep brain stimulation parameters for Parkinson's disease using functional MRI and machine learning

Commonly used for Parkinson’s disease (PD), deep brain stimulation (DBS) produces marked clinical benefits when optimized. However, assessing the large number of possible stimulation settings (i.e., programming) requires numerous clinic visits. Here, we examine whether functional magnetic resonance imaging (fMRI) can be used to predict optimal stimulation settings for individual patients. We analyze 3 T fMRI data prospectively acquired as part of an observational trial in 67 PD patients using optimal and non-optimal stimulation settings. Clinically optimal stimulation produces a characteristic fMRI brain response pattern marked by preferential engagement of the motor circuit. Then, we build a machine learning model predicting optimal vs. non-optimal settings using the fMRI patterns of 39 PD patients with a priori clinically optimized DBS (88% accuracy). The model predicts optimal stimulation settings in unseen datasets: a priori clinically optimized and stimulation-naïve PD patients. We propose that fMRI brain responses to DBS stimulation in PD patients could represent an objective biomarker of clinical response. Upon further validation with additional studies, these findings may open the door to functional imaging-assisted DBS programming.

Deep brain stimulation programming for Parkinson’s disease entails the assessment of a large number of possible simulation settings, requiring numerous clinic visits after surgery. Here, the authors show that patterns of functional MRI can predict the optimal stimulation settings.

Recent Progress on Bioresorbable Passive Electronic Devices and Systems

Bioresorbable electronic devices and/or systems are of great appeal in the field of biomedical engineering due to their unique characteristics that can be dissolved and resorbed after a predefined period, thus eliminating the costs and risks associated with the secondary surgery for retrieval. Among them, passive electronic components or systems are attractive for the clear structure design, simple fabrication process, and ease of data extraction. This work reviews the recent progress on bioresorbable passive electronic devices and systems, with an emphasis on their applications in biomedical engineering. Materials strategies, device architectures, integration approaches, and applications of bioresorbable passive devices are discussed. Furthermore, this work also overviews wireless passive systems fabricated with the combination of various passive components for vital sign monitoring, drug delivering, and nerve regeneration. Finally, we conclude with some perspectives on future fundamental studies, application opportunities, and remaining challenges of bioresorbable passive electronics.

Early decreases in cortical mid-gamma peaks coincide with the onset of motor deficits and precede exaggerated beta build-up in rat models for Parkinson's disease

Evidence suggests that exaggerated beta range local field potentials (LFP) in basal ganglia-thalamocortical circuits constitute an important biomarker for feedback for deep brain stimulation in Parkinson's disease patients, although the role of this phenomenon in triggering parkinsonian motor symptoms remains unclear. A useful model for probing the causal role of motor circuit LFP synchronization in motor dysfunction is the unilateral dopamine cell-lesioned rat, which shows dramatic motor deficits walking contralaterally to the lesion but can walk steadily ipsilaterally on a circular treadmill. Within hours after 6-OHDA injection, rats show marked deficits in ipsilateral walking with early loss of significant motor cortex (MCx) LFP peaks in the mid-gamma 41-45 Hz range in the lesioned hemisphere; both effects were reversed by dopamine agonist administration. Increases in MCx and substantia nigra pars reticulata (SNpr) coherence and LFP power in the 29-40 Hz range emerged more gradually over 7 days, although without further progression of walking deficits. Twice-daily chronic dopamine antagonist treatment induced rapid onset of catalepsy and also reduced MCx 41-45 Hz LFP activity at 1 h, with increases in MCx and SNpr 29-40 Hz power/coherence emerging over 7 days, as assessed during periods of walking before the morning treatments. Thus, increases in high beta power in these parkinsonian models emerge gradually and are not linearly correlated with motor deficits. Earlier changes in cortical circuits, reflected in the rapid decreases in MCx LFP mid-gamma LFP activity, may contribute to evolving plasticity supporting increased beta range synchronized activity in basal ganglia-thalamocortical circuits after loss of dopamine receptor stimulation.

Movement-related changes in pallidocortical synchrony differentiate action execution and observation in humans

OBJECTIVE

Suppression of local and network alpha and beta oscillations in the human basal ganglia-thalamocortical (BGTC) circuit is a prominent feature of movement, including suppression of local alpha/beta power, cross-region beta phase coupling, and cortical and subcortical phase-amplitude coupling (PAC). We hypothesized that network-level coupling is more directly related to movement execution than local power changes, given the role of pathological network hypersynchrony in movement disorders such as Parkinson disease (PD). Understanding the specificity of these movement-related signals is important for designing novel therapeutics.

METHODS

We recorded globus pallidus internus (GPi) and motor cortical local field potentials during movement execution, passive movement observation and rest in 12 patients with PD undergoing deep brain stimulator implantation.

RESULTS

Local alpha/beta power is suppressed in the globus pallidus and motor cortex during both action execution and action observation, although less so during action observation. In contrast, pallidocortical phase synchrony and GPi and motor cortical alpha/beta-gamma PAC are suppressed only during action execution.

CONCLUSIONS

The functional dissociation across tasks in pallidocortical network activity suggests a particularly important role of network coupling in motor execution.

SIGNIFICANCE

Network level recordings provide important specificity in differentiating motor behavior and may provide significant value for future closed loop therapies.

Coordinated Reset Vibrotactile Stimulation Induces Sustained Cumulative Benefits in Parkinson's Disease

BACKGROUND

Abnormal synchronization of neuronal activity in dopaminergic circuits is related to motor impairment in Parkinson's disease (PD). Vibrotactile coordinated reset (vCR) fingertip stimulation aims to counteract excessive synchronization and induce sustained unlearning of pathologic synaptic connectivity and neuronal synchrony. Here, we report two clinical feasibility studies that examine the effect of regular and noisy vCR stimulation on PD motor symptoms. Additionally, in one clinical study (study 1), we examine cortical beta band power changes in the sensorimotor cortex. Lastly, we compare these clinical results in relation to our computational findings.

METHODS

Study 1 examines six PD patients receiving noisy vCR stimulation and their cortical beta power changes after 3 months of daily therapy. Motor evaluations and at-rest electroencephalographic (EEG) recordings were assessed off medication pre- and post-noisy vCR. Study 2 follows three patients for 6+ months, two of whom received daily regular vCR and one patient from study 1 who received daily noisy vCR. Motor evaluations were taken at baseline, and follow-up visits were done approximately every 3 months. Computationally, in a network of leaky integrate-and-fire (LIF) neurons with spike timing-dependent plasticity, we study the differences between regular and noisy vCR by using a stimulus model that reproduces experimentally observed central neuronal phase locking.

RESULTS

Clinically, in both studies, we observed significantly improved motor ability. EEG recordings observed from study 1 indicated a significant decrease in off-medication cortical sensorimotor high beta power (21-30 Hz) at rest after 3 months of daily noisy vCR therapy. Computationally, vCR and noisy vCR cause comparable parameter-robust long-lasting synaptic decoupling and neuronal desynchronization.

CONCLUSION

In these feasibility studies of eight PD patients, regular vCR and noisy vCR were well tolerated, produced no side effects, and delivered sustained cumulative improvement of motor performance, which is congruent with our computational findings. In study 1, reduction of high beta band power over the sensorimotor cortex may suggest noisy vCR is effectively modulating the beta band at the cortical level, which may play a role in improved motor ability. These encouraging therapeutic results enable us to properly plan a proof-of-concept study.

The development of an implantable deep brain stimulation device with simultaneous chronic electrophysiological recording and stimulation in humans

Deep brain stimulation (DBS) is used to treat a wide array of neurologic conditions. However, traditional programming of stimulation parameters relies upon short term subjective observation of patient symptoms and undesired stimulation effects while in the clinic. To gain a more objective measure of the neuronal activity that contributes to patient symptoms and response to treatment, there is a clear need for a fully-implantable DBS system capable of chronically recording patient-specific electrophysiological biomarker signals over time. By providing an objective correlate of a patient's disease and response to treatment, this capability has the potential to improve therapeutic benefit while preventing undesirable side effects. Herein, the engineering and capabilities of the Percept PC, the first FDA-approved, fully-implantable DBS device capable of nearly-simultaneous electrophysiological recordings and stimulation, are discussed. The device's ability to chronically record local field potentials (LFPs) at implanted DBS leads was validated in patients with neurological disorders. Lastly, the electrophysiological activity correlates of clinically relevant patient-reported events are presented. While FDA approved for conditions such as Parkinson's disease, essential tremor, dystonia, obsessive-compulsive disorder, and epilepsy, chronic electrophysiological recordings in humans has broad applications within basic science and clinical practice beyond DBS, offering a wealth of information related to normal and abnormal neurophysiology within distinct brain areas.

Modulation of beta bursts in subthalamic sensorimotor circuits predicts improvement in bradykinesia

No biomarker of Parkinson's disease exists that allows clinicians to adjust chronic therapy, either medication or deep brain stimulation, with real-time feedback. Consequently, clinicians rely on time-intensive, empirical, and subjective clinical assessments of motor behaviour and adverse events to adjust therapies. Accumulating evidence suggests that hypokinetic aspects of Parkinson's disease and their improvement with therapy are related to pathological neural activity in the beta band (beta oscillopathy) in the subthalamic nucleus. Additionally, effectiveness of deep brain stimulation may depend on modulation of the dorsolateral sensorimotor region of the subthalamic nucleus, which is the primary site of this beta oscillopathy. Despite the feasibility of utilizing this information to provide integrated, biomarker-driven precise deep brain stimulation, these measures have not been brought together in awake freely moving individuals. We sought to directly test whether stimulation-related improvements in bradykinesia were contingent on reduction of beta power and burst durations, and/or the volume of the sensorimotor subthalamic nucleus that was modulated. We recorded synchronized local field potentials and kinematic data in 16 subthalamic nuclei of individuals with Parkinson's disease chronically implanted with neurostimulators during a repetitive wrist-flexion extension task, while administering randomized different intensities of high frequency stimulation. Increased intensities of deep brain stimulation improved movement velocity and were associated with an intensity-dependent reduction in beta power and mean burst duration, measured during movement. The degree of reduction in this beta oscillopathy was associated with the improvement in movement velocity. Moreover, the reduction in beta power and beta burst durations was dependent on the theoretical degree of tissue modulated in the sensorimotor region of the subthalamic nucleus. Finally, the degree of attenuation of both beta power and beta burst durations, together with the degree of overlap of stimulation with the sensorimotor subthalamic nucleus significantly explained the stimulation-related improvement in movement velocity. The above results provide direct evidence that subthalamic nucleus deep brain stimulation-related improvements in bradykinesia are related to the reduction in beta oscillopathy within the sensorimotor region. With the advent of sensing neurostimulators, this beta oscillopathy combined with lead location could be used as a marker for real-time feedback to adjust clinical settings or to drive closed-loop deep brain stimulation in freely moving individuals with Parkinson's disease.

Mechanomyography and acceleration show interlimb asymmetries in Parkinson patients without tremor compared to controls during a unilateral motor task

The mechanical muscular oscillations are rarely the objective of investigations regarding the identification of a biomarker for Parkinson's disease (PD). Therefore, the aim of this study was to investigate whether or not this specific motor output differs between PD patients and controls. The novelty is that patients without tremor are investigated performing a unilateral isometric motor task. The force of armflexors and the forearm acceleration (ACC) were recorded as well as the mechanomyography of the biceps brachii (MMGbi), brachioradialis (MMGbra) and pectoralis major (MMGpect) muscles using a piezoelectric-sensor-based system during a unilateral motor task at 70% of the MVIC. The frequency, a power-frequency-ratio, the amplitude variation, the slope of amplitudes and their interlimb asymmetries were analysed. The results indicate that the oscillatory behavior of muscular output in PD without tremor deviates from controls in some parameters: Significant differences appeared for the power-frequency-ratio (p = 0.001, r = 0.43) and for the amplitude variation (p = 0.003, r = 0.34) of MMGpect. The interlimb asymmetries differed significantly concerning the power-frequency-ratio of MMGbi (p = 0.013, r = 0.42) and MMGbra (p = 0.048, r = 0.39) as well as regarding the mean frequency (p = 0.004, r = 0.48) and amplitude variation of MMGpect (p = 0.033, r = 0.37). The mean (M) and variation coefficient (CV) of slope of ACC differed significantly (M: p = 0.022, r = 0.33; CV: p = 0.004, r = 0.43). All other parameters showed no significant differences between PD and controls. It remains open, if this altered mechanical muscular output is reproducible and specific for PD.

Cortical hemodynamic mapping of subthalamic nucleus deep brain stimulation in Parkinsonian patients, using high-density functional near-infrared spectroscopy

Subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for idiopathic Parkinson's disease. Despite recent progress, the mechanisms responsible for the technique's effectiveness have yet to be fully elucidated. The purpose of the present study was to gain new insights into the interactions between STN-DBS and cortical network activity. We therefore combined high-resolution functional near-infrared spectroscopy with low-resolution electroencephalography in seven Parkinsonian patients on STN-DBS, and measured cortical haemodynamic changes at rest and during hand movement in the presence and absence of stimulation (the ON-stim and OFF-stim conditions, respectively) in the off-drug condition. The relative changes in oxyhaemoglobin [HbO], deoxyhaemoglobin [HbR], and total haemoglobin [HbT] levels were analyzed continuously. At rest, the [HbO], [HbR], and [HbT] over the bilateral sensorimotor (SM), premotor (PM) and dorsolateral prefrontal (DLPF) cortices decreased steadily throughout the duration of stimulation, relative to the OFF-stim condition. During hand movement in the OFF-stim condition, [HbO] increased and [HbR] decreased concomitantly over the contralateral SM cortex (as a result of neurovascular coupling), and [HbO], [HbR], and [HbT] increased concomitantly in the dorsolateral prefrontal cortex (DLPFC)-suggesting an increase in blood volume in this brain area. During hand movement with STN-DBS, the increase in [HbO] was over the contralateral SM and PM cortices was significantly lower than in the OFF-stim condition, as was the decrease in [HbO] and [HbT] in the DLPFC. Our results indicate that STN-DBS is associated with a reduction in blood volume over the SM, PM and DLPF cortices, regardless of whether or not the patient is performing a task. This particular effect on cortical networks might explain not only STN-DBS's clinical effectiveness but also some of the associated adverse effects.

Stimulation of the right entorhinal white matter enhances visual memory encoding in humans

BACKGROUND

While deep brain stimulation has been successful in treating movement disorders, such as in Parkinson's disease, its potential application in alleviating memory disorders is inconclusive.

OBJECTIVE/HYPOTHESIS

We investigated the role of the location of the stimulating electrode on memory improvement and hypothesized that entorhinal white versus gray matter stimulation would have differential effects on memory.

METHODS

Intracranial electrical stimulation was applied to the entorhinal area of twenty-two participants with already implanted electrodes as they completed visual memory tasks.

RESULTS

We found that stimulation of right entorhinal white matter during learning had a beneficial effect on subsequent memory, while stimulation of adjacent gray matter or left-sided stimulation was ineffective. This finding was consistent across three different visually guided memory tasks.

CONCLUSIONS

Our results highlight the importance of precise stimulation site on modulation of human hippocampal-dependent memory and suggest that stimulation of afferent input into the right hippocampus may be an especially promising target for enhancement of visual memory.

Cross-frequency coupling between gamma oscillations and deep brain stimulation frequency in Parkinson's disease

The disruption of pathologically enhanced beta oscillations is considered one of the key mechanisms mediating the clinical effects of deep brain stimulation on motor symptoms in Parkinson's disease. However, a specific modulation of other distinct physiological or pathological oscillatory activities could also play an important role in symptom control and motor function recovery during deep brain stimulation. Finely tuned gamma oscillations have been suggested to be prokinetic in nature, facilitating the preferential processing of physiological neural activity. In this study, we postulate that clinically effective high-frequency stimulation of the subthalamic nucleus imposes cross-frequency interactions with gamma oscillations in a cortico-subcortical network of interconnected regions and normalizes the balance between beta and gamma oscillations. To this end we acquired resting state high-density (256 channels) EEG from 31 patients with Parkinson's disease who underwent deep brain stimulation to compare spectral power and power-to-power cross-frequency coupling using a beamformer algorithm for coherent sources. To show that modulations exclusively relate to stimulation frequencies that alleviate motor symptoms, two clinically ineffective frequencies were tested as control conditions. We observed a robust reduction of beta and increase of gamma power, attested in the regions of a cortical (motor cortex, supplementary motor area, premotor cortex) and subcortical network (subthalamic nucleus and cerebellum). Additionally, we found a clear cross-frequency coupling of narrowband gamma frequencies to the stimulation frequency in all of these nodes, which negatively correlated with motor impairment. No such dynamics were revealed within the control posterior parietal cortex region. Furthermore, deep brain stimulation at clinically ineffective frequencies did not alter the source power spectra or cross-frequency coupling in any region. These findings demonstrate that clinically effective deep brain stimulation of the subthalamic nucleus differentially modifies different oscillatory activities in a widespread network of cortical and subcortical regions. Particularly the cross-frequency interactions between finely tuned gamma oscillations and the stimulation frequency may suggest an entrainment mechanism that could promote dynamic neural processing underlying motor symptom alleviation.

Postmortem Dissections of Common Targets for Lesion and Deep Brain Stimulation Surgeries

BACKGROUND

The subthalamic nucleus (STN), globus pallidus internus (GPi), and pedunculopontine nucleus (PPN) are effective targets for deep brain stimulation (DBS) in many pathological conditions. Previous literature has focused on appropriate stimulation targets and their relationships with functional neuroanatomic pathways; however, comprehensive anatomic dissections illustrating these nuclei and their connections are lacking. This information will provide insight into the anatomic basis of stimulation-induced DBS benefits and side effects.

OBJECTIVE

To combine advanced cadaveric dissection techniques and ultrahigh field magnetic resonance imaging (MRI) to explore the anatomy of the STN, GPi, and PPN with their associated fiber pathways.

METHODS

A total of 10 cadaveric human brains and 2 hemispheres of a cadaveric head were examined using fiber dissection techniques. The anatomic dissections were compared with 11.1 Tesla (T) structural MRI and 4.7 T MRI fiber tractography.

RESULTS

The extensive connections of the STN (caudate nucleus, putamen, medial frontal cortex, substantia innominata, substantia nigra, PPN, globus pallidus externus (GPe), GPi, olfactory tubercle, hypothalamus, and mammillary body) were demonstrated. The connections of GPi to the thalamus, substantia nigra, STN, amygdala, putamen, PPN, and GPe were also illustrated. The PPN was shown to connect to the STN and GPi anteriorly, to the cerebellum inferiorly, and to the substantia nigra anteriorly and superiorly.

CONCLUSION

This study demonstrates connections using combined anatomic microdissections, ultrahigh field MRI, and MRI tractography. The anatomic findings are analyzed in relation to various stimulation-induced clinical effects. Precise knowledge of neuroanatomy, anatomic relationships, and fiber connections of the STN, GPi, PPN will likely enable more effective targeting and improved DBS outcomes.

A Pilot Study on Data-Driven Adaptive Deep Brain Stimulation in Chronically Implanted Essential Tremor Patients

Deep brain stimulation (DBS) is an established therapy for Parkinson's disease (PD) and essential-tremor (ET). In adaptive DBS (aDBS) systems, online tuning of stimulation parameters as a function of neural signals may improve treatment efficacy and reduce side-effects. State-of-the-art aDBS systems use symptom surrogates derived from neural signals-so-called neural markers (NMs)-defined on the patient-group level, and control strategies assuming stationarity of symptoms and NMs. We aim at improving these aDBS systems with (1) a data-driven approach for identifying patient- and session-specific NMs and (2) a control strategy coping with short-term non-stationary dynamics. The two building blocks are implemented as follows: (1) The data-driven NMs are based on a machine learning model estimating tremor intensity from electrocorticographic signals. (2) The control strategy accounts for local variability of tremor statistics. Our study with three chronically implanted ET patients amounted to five online sessions. Tremor quantified from accelerometer data shows that symptom suppression is at least equivalent to that of a continuous DBS strategy in 3 out-of 4 online tests, while considerably reducing net stimulation (at least 24%). In the remaining online test, symptom suppression was not significantly different from either the continuous strategy or the no treatment condition. We introduce a novel aDBS system for ET. It is the first aDBS system based on (1) a machine learning model to identify session-specific NMs, and (2) a control strategy coping with short-term non-stationary dynamics. We show the suitability of our aDBS approach for ET, which opens the door to its further study in a larger patient population.

Deep brain stimulation: a review of the open neural engineering challenges

OBJECTIVE

Deep brain stimulation (DBS) is an established and valid therapy for a variety of pathological conditions ranging from motor to cognitive disorders. Still, much of the DBS-related mechanism of action is far from being understood, and there are several side effects of DBS whose origin is unclear. In the last years DBS limitations have been tackled by a variety of approaches, including adaptive deep brain stimulation (aDBS), a technique that relies on using chronically implanted electrodes on 'sensing mode' to detect the neural markers of specific motor symptoms and to deliver on-demand or modulate the stimulation parameters accordingly. Here we will review the state of the art of the several approaches to improve DBS and summarize the main challenges toward the development of an effective aDBS therapy.

APPROACH

We discuss models of basal ganglia disorders pathogenesis, hardware and software improvements for conventional DBS, and candidate neural and non-neural features and related control strategies for aDBS.

MAIN RESULTS

We identify then the main operative challenges toward optimal DBS such as (i) accurate target localization, (ii) increased spatial resolution of stimulation, (iii) development of in silico tests for DBS, (iv) identification of specific motor symptoms biomarkers, in particular (v) assessing how LFP oscillations relate to behavioral disfunctions, and (vi) clarify how stimulation affects the cortico-basal-ganglia-thalamic network to (vii) design optimal stimulation patterns.

SIGNIFICANCE

This roadmap will lead neural engineers novel to the field toward the most relevant open issues of DBS, while the in-depth readers might find a careful comparison of advantages and drawbacks of the most recent attempts to improve DBS-related neuromodulatory strategies.

EEG and MEG primers for tracking DBS network effects

Deep brain stimulation (DBS) is an effective treatment method for a range of neurological and psychiatric disorders. It involves implantation of stimulating electrodes in a precisely guided fashion into subcortical structures and, at a later stage, chronic stimulation of these structures with an implantable pulse generator. While the DBS surgery makes it possible to both record brain activity and stimulate parts of the brain that are difficult to reach with non-invasive techniques, electroencephalography (EEG) and magnetoencephalography (MEG) provide complementary information from other brain areas, which can be used to characterize brain networks targeted through DBS. This requires, however, the careful consideration of different types of artifacts in the data acquisition and the subsequent analyses. Here, we review both the technical issues associated with EEG/MEG recordings in DBS patients and the experimental findings to date. One major line of research is simultaneous recording of local field potentials (LFPs) from DBS targets and EEG/MEG. These studies revealed a set of cortico-subcortical coherent networks functioning at distinguishable physiological frequencies. Specific network responses were linked to clinical state, task or stimulation parameters. Another experimental approach is mapping of DBS-targeted networks in chronically implanted patients by recording EEG/MEG responses during stimulation. One can track responses evoked by single stimulation pulses or bursts as well as brain state shifts caused by DBS. These studies have the potential to provide biomarkers for network responses that can be adapted to guide stereotactic implantation or optimization of stimulation parameters. This is especially important for diseases where the clinical effect of DBS is delayed or develops slowly over time. The same biomarkers could also potentially be utilized for the online control of DBS network effects in the new generation of closed-loop stimulators that are currently entering clinical use. Through future studies, the use of network biomarkers may facilitate the integration of circuit physiology into clinical decision making.

Neuromodulation effects of deep brain stimulation on beta rhythm: A longitudinal local field potential study

BACKGROUND

Deep brain stimulation (DBS) holds great promise in treating various brain diseases but its chronic therapeutic mechanisms are unclear.

OBJECTIVE

To explore the immediate and chronic effects of DBS on brain oscillations, and understand how different sub-bands of oscillations may be related to symptom improvement in Parkinson's patients.

METHODS

We carried out a longitudinal study to examine the effects of DBS on local field potentials recorded by sensing-enabled neurostimulators in the subthalamic nuclei of Parkinson's patients, using a novel block-design stimulation paradigm.

RESULTS

DBS significantly suppressed beta activity (13-35Hz) but the suppression effect appeared to gradually attenuate during a 6-month follow-up period after surgery (p = 0.002). However, beta suppression did not attenuate after repeated stimulation over several minutes (p > 0.110), suggesting that the changes in beta suppression may reflect a slow reconfiguration of neural pathways instead of habituation. Suppression of beta was also associated with clinical symptom improvement across subjects. Importantly, symptom-relevant features fell within the high beta band at month 1 but shifted to the low beta band at month 6, indicating that the high beta and the low beta oscillations may play different functional roles and respond differently to stimulation over the long-term treatment.

CONCLUSION

These data may advance understanding of chronic DBS effects on beta oscillations and their association with clinical improvement, offering novel insights to the therapeutic mechanisms of DBS.